In the last few decades, non-traditional machining made the machining
process easier than the traditional machining method. Electric discharge
machining (EDM) is one of the most prominent methods of non-traditional
machining processes. By the use of EDM, a complex profile and high hardness
materials can be easily machined, which cannot easily be machined by the
traditional machining method. EDM is widely used by the industries. This
paper investigates an experiment with the cryogenically treated copper
electrode and an ordinary copper electrode with various input parameters
like the electrode rotation, gap voltage and discharge current for an EN24 (a high-strength and wear-resistant steel)
material. An experiment was performed with electric discharge machining.
Designs of an experiment are carried out using the Taguchi approach. An
orthogonal L16 array prepared and used the different combination of the
three input parameters (current, electrode rotation and gap voltage) to find
an optimum value of the factors. The output factors are the overcut (OC),
the tool wear rate (TWR) and surface roughness (Ra). The optimal level and importance
levels of each of these parameters are obtained statically using an analysis-of-variance (ANOVA) table through the analysis of the S/N ratio. The study also compares the
theoretical and experimental values of the overcut, tool wear rate and surface
roughness for traditional and non-traditional EDM. The following research
finds optimal or dominating factors (current and rotational speed) for
the TWR and Ra in both traditional and non-traditional electric discharge
machining; moreover there was a reduction of approximately 9 % in overcut, 13.25 % in
the tool wear rate and 15.75 % in surface roughness for the deep cryogenic and non-traditional machining process.

1Introduction

The electrical discharge machining (EDM) is widely used to machine a very hard
surface material at a low cost and with fewer hardness tools (Huang et al., 2003).
This machining operation was improved and upgraded with time (Habib and Sameh,
2009). In the 1930s, EDM came into existence for the first time for a machining
purpose, but due to overheating, lower material removal rate (MRR) and lower quality of the machined
surface, it could not be used on a large scale. So to overcome this problem,
the researchers worked continuously after the introduction of the EDM
to improve the quality of the machining operation, improving surface finish,
the material removal rate, etc. In the EDM process, removal of metal takes place
due to the erosion carried by the sparks occurring between the tool and work
piece (Srivastava and Panday, 2011). At present, EDM is the most widely used
technique for high-precision machining of all types of conductive metals, irrespective of hardness. It is also used in the automobile industry,
in aerospace and in the farm industry (Shazarel et al., 2009). The initial cost of
EDM machining is high, but with the selection of the optimal parameter levels,
its wastage and operating cost decrease with quality improvements (Kapoor et
al., 2012). The EDM process continuously analysed with different levels of
parameters to improve the quality of machining output. In this present
research, machine factors like the overcut, TWR and Ra are taken as
machining output (response) parameters. So for the better dimensioning and
quality, TWR, Ra and overcut size should be at a minimum (B. R. Kumar et al., 2014).

Figure 1

Cryogenic treatment and tempering (CTT; Singh and Singh, 2011).

Kumar and M (2014) performed an experiment on a cryogenic cooled electrode
and found a more beneficial effect on the machining operation than the
conventional electrode. Gill and Singh (2010) investigated the effect of
deep cryogenic treatment on the Ti 6246 alloy for a machining purpose. The
investigators found a higher material removal rate and lower tool wear
rate. Srivastava and Panday (2013) conducted an experiment with the process
parameters like the pulse in time, current, duty cycle and voltage for response
factors like the tool wear rate, material removal rate and surface roughness
with a cryogenically treated electrode. They revealed that the current, pulse in
time and duty cycle have a significant effect on the tool wear and material
removal rate. In this research paper, the cryogenic treatment of an
electrode is examined. Yildiz and Nalbant (2008) made an
improvement in tool life by using the cryogenic process in the cutting
operation. Abdulkareem et al. (2009) reveal that surface roughness is
reduced by using a cryogenically cooled electrode during machining. Kumar
and M (2015) carried out an investigation with machining parameters including
the pulse in time, gap voltage and current for output responses comprised of the
material removal rate, electrode wear rate, and electrode temperature for
conventional and cryogenic EDM. The pulse in time has the most significant
factor, and moreover, electrode wear was reduced to 18 % by the cryogenic
electrode.

2Experiment set-up and details2.1Material details

EDM is applicable to electrically conductive materials. In this paper, the
research is conducted on a EN24 steel work piece. This material is used for
variety of parts, dyes, gears, shafts and moulds. EN24 steel is widely used
in power and transmission due to its high tensile strength. In this experiment
a 10 mm diameter of the copper electrode is used. The weight of the electrode and work
piece was measured with the help of a weighting machine. Moreover thickness and
the diameter of the work piece and tool are measured with a digital micrometer.

Table 1

Chemical composition of material.

ElementCCrMnSiSPCuNi

Weight (%)0.37090.94750.591250.26590.019340.010831.2691.253

The work piece and electrode were submerged in dielectric fluid, which is shown in
Fig. 2. The dielectric fluid is the insulator of electricity. Therefore this
insulation property of the dielectric produces a required limit of the potential
difference between the tool and work piece that is necessary for spark
generation (Zhiguang et al., 2015). The gap difference between the work piece and
electrode was maintained with the help of the servo mechanism. This mechanism
maintains a gap of about 0.03 mm. In this mechanism, operation length and the diameter of
the work piece are respectively 28 and 15 mm. In this machining, the dielectric
fluid is kerosene oil (Gill and Singh, 2010). The electrode material used in EDM
is the copper electrode, having 100 HB (HB – Brinell hardness unit) hardness and a electrical resistivity
of 9 µΩcm. The compositions of work pieces and electrodes are
mentioned in Tables 1 and 2. In this experiment, two types of
cylindrical copper electrodes are used. Both electrodes are 20 mm in length and have a
10 mm diameter. One electrode is cryogenically treated, and the other is
not cryogenically treated. Copper metal has low electrical and thermal
resistance. Due to this, it transfers more energy to the work piece.

Table 2

Chemical composition of electrode.

ElementCuAgPbSO

Weight (%)99.90.0150.0050.0080.004

2.1.1Mechanism of EDM

The D.C (direct current) supply of a high ampere current at low voltage is given to the electrode.
This permits the spark between the electrode and the work piece through the
dielectric fluid (Singh and Singh, 2011). This spark generates high heat
between the electrode and work piece. This heat is sufficient for eroding or melting the
material from the work piece. The molten particles are flushed with the flow of
a dielectric fluid. This flow is circulated with the help of a pump. In this
experiment both electrodes connected with negative polarity and the work piece in
positive polarity, as shown in Fig. 2.

Figure 2

Overcut (Habib and Samesh, 2009).

2.2Design of experiment2.2.1Taguchi technique

The Taguchi technique is very helpful for optimizing the results. It is mostly used
by manufacturing engineers, scientists and quality-assurance experts. The
main target of the Taguchi method is to set up an experiment and to develop
superior performances. Classical experimental design methods are too
complex and not easy to use. Furthermore, a large number of experiments have
to be carried out as the number of the process parameters increases. Instead
of testing all possible combinations like the factorial design, the Taguchi
method is applied. So to solve this important task, the Taguchi method uses a
special design of the orthogonal array to study the entire parameter space with
only a small number of experiments. An experimental design scheme of
statistical experiments that uses orthogonal arrays, however, entails the
following considerations and consequences.

The orthogonal array focusses only on a main effect design. An orthogonal
array has been used by researchers for the last few years to determine the
minimum number of experiments. The selection of orthogonal array is one of
the important sets for performing the experiments to determine the optimum
level for each parameter.

2.2.2Analysis of variance

Analysis of variance (ANOVA) is selected for choosing new parameter
values to optimize the performance characteristic at 95 %. The F value is used
to check the significance of values. The probability of the F value which
exceeds the calculated F value due to the noise is given by the P value. The
verification test is used to verify whether this approximation is
satisfactory and valid.

2.2.3Signal-to-noise ratio

The experimental results are then transformed into a signal-to-noise (S/N)
ratio. The S/N ratio is used to measure the deviation of the performance
characteristics from the desired values. The categories of performance
characteristics in the analysis of the S/N ratio depend on output
parameters being controlled. The S/N ratio is used to measure the quality
characteristic, such as larger being better, nominal being the best or smaller being
better.

The objective of this research is to minimize the tool wear rate, surface
roughness and overcut. In this research paper S/N ratios of the overcut, TWR and
Ra for both the cryogenically treated and untreated electrode are “smaller is
better”:
S/N=-10log⁡∑(y2)/n,
where y is responses for the given factor level combination and
n is the number of responses in the factor level combination.

2.3Cryogenic treatment

Cryogenical treatment of the electrode is performed in a cryogenic chamber, which is shown in Fig. 1. In this operation liquid nitrogen gas is used to
perform the cryogenic treatment. The cryogenic treatment (CT) is a slow
cooling process, with a cool-down rate of approximately 2–3 ∘C min-1 to room temperature from the temperature of liquid nitrogen
(-130∘C min-1). After reaching the temperature of an electrode at
such a limit, the material is sunk at a same temperature for approximately
1 d. After that, the electrode is removed from liquid nitrogen and goes
through the heat treatment process. In this heat treatment process,
electrode heats up from room temperature to above 100 ∘C and cools
down at room temperature in ambient air (Gill and Singh, 2010; Dhanachezian
et al., 2011; Singh et al., 2015). In this treatment, phase transformation
occurs, and this transformation increases the hardness of the tool material
when austenite starts converting into martensite; but during this
transformation, all austenite did not convert into martensite (Kumar et
al., 2012; Kalsi et al., 2010). Therefore, large and non-uniform carbides
are produced with residual stress and a brittle structure, which are shown in
Fig. 6a. These non-uniform carbides affect the tool life.

Figure 3

Untreated and treated electrode microstructure.

Therefore, to control on this problem, the tool is tempered after
cryogenic treatments, which is shown in Fig. 1.

Cryogenically treated with tempering (CTT) of the electrode microstructure.

The tempering process helps in reducing the stress and brittleness. Moreover it
transforms the retained austenite into martensite with the formation of a fine
and uniform chromium carbide microstructure. The
untreated, cryogenically treated and deep cryogenically treated with tempering (CTT) microstructure analyses are shown in Figs. 3, 4 and 5 respectively. The microstructure in CTT is more uniform, small in
size and symmetrical than the cryogenically treated and the non-cryogenic electrode. In Fig. 5
microstructures are more uniform than in Figs. 3 and 4. The
precipitation of the fine carbide particle structure of carbide shown in Fig. 6b is more fine and uniform than in Fig. 6a. So this fine carbide
improves toughness, fatigue resistance, hardness, wear resistance, surface
smoothness and dimensional stability. Therefore CTT is more significant than CT.

Figure 6

Scanning electron microscope (SEM) images of (a) CT and (b) CTT.

In these cases (deep cryogenically treated and untreated), the same level and
parameters are used. During the operation in EDM, some material was removed from
the tool and as well as from the work piece, but the material removal rate from the work
piece is very high compared to the tool wear rate because the work
piece is connected with positive polarity, and therefore a large amount of heat is generated
on the work piece during sparking (Kumar et al., 2012; Kalsi et al., 2010).
The Taguchi design is used to perform the experiment, and afterwards ANOVA is used
for analysis. In this research, L16 is used for the experiment. There
are three input factors (current, electrode rotation and voltage)
with four levels that are given in Table 3. In the literature there
is much less work done with electrode rotation with deep cryogenic
treatment. There is no research in the literature with these levels
that has been selected for a research paper on EN24 steel. Due to this, these
levels are selected for traditional and non-traditional EDM.

Quality is an important factor that customers use to evaluate a product or
service. So the new quality-control and improvement programmes have to make
their products more acceptable to the customers. On the other hand, a customer
evaluates a product performance based on a number of diverse qualitative
characteristics. To improve the rational decision-making, the evaluations of
various attributes should be combined to give a composite index. Such a
composite index is known as the utility of a product. The sum of utilities of
each quality attribute represents the overall utility of a product. It is
difficult to obtain the best combination of process parameters when there
are multiple responses. If xi represents the measure of effectiveness of
the ith process response characteristic and n represents the number of responses, then
the overall utility function can be written as
U(x1,x2…xn)=∑i=1nWiUi(Xi),
where ∑i=1nWi=1Wi is the weight assigned to the ith response characteristic.

2.5Results and discussion

In EDM, the cavity is produced with the help of a spark that is generated
between the electrode and work piece. Therefore the overcut is the difference between
the size of the cavity on the work piece and the diametrical size of the
electrode:
Over cut (OC)=(Dcs-De)/2,
where Dcs is the diameter of the cavity, and De is the diameter of the electrode.

Surface roughness is measured with the help of a portable Profilometer
Talysurf. Tables 4 and 5 represent the values of the overcut, tool
wear rate and surface roughness for conventional EDM and the deep cryogenic
electrode and cryogenically treated EDM (CCT) respectively. For the tool wear rate,

Tw1-tw1q⋅Tmm3min-1,
where Tw1 is the weight of the electrode before machining, tw1 is the weight of
the electrode after machining, q is the density of the electrode and T is time.

Tables 8 and 9 represent the ranked value of an input variable like
the current, rotation and voltage for an output variable or response variable for
the untreated electrode and deep cryogenically treated electrode. In this table
the current has a high ranked value (high impact) for the tool wear rate and surface
roughness, but in the case of the overcut, the current has much less impact.

The graphs are made with the help of Minitab software. These graphs
highlight the process parameters and different optimal levels for machining.

Figure 9

Current and voltage relation of OC for the non-cryogenic tool.

Figure 10

Rotation and voltage relation of OC for the non-cryogenic tool.

Figure 11

Ra S/N ratio graph for the non-cryogenic tool.

Figure 12

OC1S/N graph for the cryogenic tool.

These optimal parameters are the current (130), rotation of electrode (1100) and
voltage (165 V) for an ordinary electrode (non-cryogenically treated electrode).
These levels give an optimal value of the overcut (rough cut) that is shown in
Fig. 7.

Figure 13

TWR1S/N graph for the cryogenic tool.

Figure 14

Ra1S/N for the cryogenic tool.

Figure 15

Rotation and voltage relation of OC1 for the cryogenic tool.

Figure 16

Current and voltage relation of OC1 for the cryogenic tool.

This figure helps in selecting the optimal levels (having a small value of the S/N
ratio) of different factors. Similarly same factors and levels are set up
for the next experiments for the cryogenically treated electrode. The
results are seen after measuring the values of the overcut, and S/N graphs are shown in Fig. 12 after
analysis. The optical parameters for a
treated electrode are the same as in the previous experiment that was performed
for an untreated electrode. On the other hand, first, optimal parameters are
observed in the case of an untreated electrode for the TWR and Ra,
and then the same levels and parameters are set up for a cryogenically treated
electrode to TWR1 and Ra1. Figures 8 and 13 show the
graphs of the TWR for the untreated and cryogenically treated electrode respectively, and
Figs. 11 and 14 represent surface roughness. In Figs. 8 and 13 there are
minimum values of the S/N ratio that are taken as optimal levels. In the case of a
current factor, 210 A has a smaller S/N ratio. In the case of the rotation factor,
2100 rpm has a smaller S/N ratio, and similarly to the case of voltage (210 V), it has a smaller
value of S/N. So these are the optimal levels of their respective factors,
and Figs. 11 and 14 show the surface roughness graphs for the normal tool and
cryogenically (deep) treated tool respectively. Figures 9, 10, 15 and 16
represent the mean overcut of deep cryogenic and normal tool with factors and
their levels. These figures shed light on more significant factors,
having a small value of the rough cut. In these figures, one factor (voltage)
remains to be fixed, and other factors (current and voltage) change.

3Validation test and an estimation of optimum responses

In this section, the optimal values of the response characteristic (overcut,
tool wear rate and surface roughness) and their levels have been
predicted for the untreated and deep cryogenically treated electrode.

The 95 % confidence intervals of confirmation experiments and the sample group
(CICE) and confidence intervals for the entire group or population
(CIPOP) are given in the following equation.

The confidence intervals of confirmation experiments are represented by
1CICE=Fα1,feVe1neff+1R.
The confidence intervals of the confirmed population are calculated from
2CIPOP=Fα1,feVeneff,neff=N1+(DOFassociatedinestimateofmeanresponcess),
where Fα(1,fe) is the F ratio at the 95 % confidence level
against DOF (degree of freedom) and the error in DOF fe, Ve is the value of error, and R is the trail number for confirmation.

After completing the above experiment, the next step is to find the
significant parameters and their importance and a validation test for traditional
EDM by using optimal levels.

3.1.1OC (overcut for non-cryogenic electrode)

In the case of untreated electrode for overcut (OC), find the predicted
values at the significant condition. The selected values of significant factors
like current (A1), electrode rotation (B1) and voltage (C3) are shown
in Fig. 7 and Table 6. The estimated mean of the response characteristic
can be determined as
ΔOC=AI+BI+CIII-TOC=1.56+1.49+1.505-1.2425=3.3125,
where TOC overall is the mean of OC in Table 4.

The confidence interval for the sample group (CICE) is at 95 % confidence, calculated from Eq. (1), where Fα(1,Fe) is the F ratio value of 5.99; Ve=2.077 (from
Table 6); and neff=N/[1+DF] and R=1, where N=16, DOF = 9 and neff=1.6.

By putting these values in Eq. (1), CICE=4.49633.
The predicted range for sample size is ΔOC-CICE<ΔOC<ΔOC+CICE=3.3175-4.49633<3.3175<3.3175+4.49633=-1.17883<3.3175<7.81383.

The confidence interval for the entire group (CIPOP) is at 95 % from
Eq. (2).

Fα(1,Fe)=5.99, Ve=2.077 and neff=1.6.
When putting these values into Eq. (2) above, CIPOP=2.7885. The predicted range for the entire group is ΔOC-CIPOP<ΔOC<ΔOC+CIPOP=3.3175-2.7885<3.3175<3.3175+2.7885=0.529<3.3175<6.106.

From the CICE and CIPOP the positive validation test is shown for
the non-cryogenically treated electrode. It shows that the mean values of the overcut for
the sample group and for the entire population lie between the limits, and
the test is then validated.

The optimal values of process variables are as follows:

The first level of the current is AI = 130 A.

The first level of the electrode rotation is BI = 1100 rpm.

The third level of the voltage is CIII = 165 V.

3.1.2TWR (tool wear rate for non-cryogenic tool)

The optimal value of TWR is predicted at significant variables. The
estimated mean of the response characteristic can be determined as
ΔTWR=AII+BIV-TTWR,
where TTWR is the overall mean of TWR in Table 4:
ΔTWR=2.475+2.1625-1.9656=2.6719.
This represents the 95 % confidence interval of the confirmation experiment (CICE) and
population (CIPOP) from the equations,

so CICE=5.455 and CIPOP=3.009.

The predicted range for sample size is ΔTWR-CICE<ΔTWR<ΔTWR+CICE=-2.7831<2.6719<8.1269.

The predicted range for entire group is ΔTWR-CIPOP<ΔTWR<ΔTWR+CIPOP=-0.3371<2.6719<5.6809.

The optimal values of process variables are as follows:

The first level of the current is AII = 210 A.

The first level of the electrode rotation is BIV = 2100 rpm.

The third level of the voltage is CII = 120 V.

3.1.3Ra (surface roughness for non-cryogenically treated tool)

The optimal value of Ra is predicted at significant variables. The estimated
mean of the response characteristic can be determined as
ΔRa=AI+BI-TRa,
where TRa is the overall mean of Ra in
Table 4:
ΔRa=3.635+3.275-2.324=4.586.
This represents the 95 % confidence interval of the confirmation experiment (CICE) and
population (CIPOP) from the equations,

so CICE=7.664 and CIPOP=4.228.

The predicted range for the sample size is ΔRa-CICE<ΔRa<ΔRa+CICE=-3.078<4.586<12.25.

The predicted range for entire group is ΔRa-CIPOP<ΔRa<ΔRa+CIPOP=0.358<4.228<8.814.

Similarly the next step is to find the significant parameters and their
importance and the validation test for non-traditional EDM by using the same
optimal levels that are used in traditional EDM.

3.2.1OC1 (overcut for deep cryogenic electrode)

In the case of OC1, find the predicted values at the significant condition.
The selected values of significant factors like the current (A1), electrode
rotation (B1) and voltage (C3) are shown in Fig. 12 and Table 7. The
estimated mean of the response characteristic can be determined as
ΔOC1=B1-TOC1,
where TOC1 is from Table 5, and
ΔOC1=1.4075-1.15187=ΔOC1=0.25563.
Now the confidence interval for the sample group (cCICE) is at the 95 %
conformation interval for the cryogenic tool.

The confidence interval for entire group (CIPOP) for the cryogenic tool can be calculated as follows.

Similarly, put the values of Fα(1,Fe), Ve and neff for
the cryogenically treated electrode into Eq. (2). Then CIPOP=2.223.

The predicted range for entire group is ΔOC1-CIPOP<ΔOC1<ΔOC1+CIPOP=-1.9673<0.25562<2.4786.

The equations show that the mean values lie within limits. Therefore the both tests
are validated. The optimal level values of factors are the same as in the overcut of
traditional EDM.

3.2.2TWR1 (tool wear rate for cryogenic tool)

The optimal value of TWR1 is predicted at significant variables. The
estimated mean of the response characteristic can be determined as
ΔTWR1=AII+BIV-TTWR1,
where
TTWR1 is the overall mean of TWR1 in Table 5:
ΔTWR1=2.3025+1.9375-1.73812=2.50188.
This represents the 95 % confidence interval of the confirmation experiment (CICE) and
population (CIPOP) from the following equations, so CICE=5.9128 and CIPOP=3.2623.

The predicted range for sample size is ΔTWR1-CICE<ΔTWR1<ΔTWR1+CICE=-3.4109<2.50188<8.4146.

The predicted range for entire group is ΔTWR1-CIPOP<ΔTWR1<ΔTWR1+CIPOP=0.7604<2.50188<5.7641.

3.2.3Ra1 (surface roughness for cryogenically treated tool)

The optimal value of Ra1 is predicted at significant variables. The
estimated mean of the response characteristic can be determined as
ΔRa=AI+BI-TRa1,
where TRa1 is the overall mean of Ra1 in Table 5:
ΔRa1=3.3+3.15-2.1093=4.3407.
This represents the 95 % confidence interval of the confirmation experiment (CICE) and
population (CIPOP) from the equations.

So CICE=9.3352 and CIPOP=5.150.

The predicted range for sample size is ΔRa1-CICE<ΔRa1<ΔRa1+CICE=-4.9945<4.3407<13.6752.

The predicted range for entire group is ΔRa1-CIPOP<ΔRa1<ΔRa1+CIPOP=-0.8093<4.3407<9.4907.

From this, CICE and CIPOP lie between the limits, and the test is validated.

For the overcut (OC), it is 1.112 - 0.00160. The current is + 0.000006, and the rotation speed is + 0.00360 V.

For the tool wear rate (TWR), it is 4.031 - 0.00541. The current is - 0.000283, and the rotation is - 0.00197 V.

For surface roughness (Ra), it is 5.75 - 0.00814. The current is - 0.000658, and the rotation is - 0.00245 V.

3.3.2The regression equation for cryogenically treated electrode

For overcut (OC1), it is 1.068 - 0.00124. The current is - 0.000038, and the rotation
speed is + 0.00316 V.

For the tool wear rate (TWR1), it is 3.837 - 0.00601. The current is - 0.000236, and the rotation is - 0.00170 V.

For surface roughness (Ra1), it is 5.27 - 0.00703. The current is - 0.000675, and the rotation is - 0.00243 V.

3.4Conformation test

To evaluate the adequacy of the proposed approach and statistical analysis, a
set of verifications is conducted on predicted values. The confirmation test
is carried out to check the reproducibility of predicted results. The predicted
results came from Eqs. (9) to (14).

By using optimal parameters in the above equation, predicted OC and OC1 are found; moreover the three (E1, E2 and E3) sets of experiments are
performed on the optimal levels (A1, B1 and C3) of parameters to find
the experimental value of OC and OC1. Plots of the S/N ratio in Figs. 7 and
12 for untreated and cryogenically treated electrode respectively
show the optimal levels for different factors. The line plots of the mean Roc (Roc – rough cut)
show the predicted value of the treated (OC1) and untreated (OC) electrode.
Figures 11 and 12 show the mean value of the overcut on the left-hand side; the bottom
side shows the value of different factors, and the right-hand side shows the
largest rank factor values. In this, both figures' current (130 V), rotation
speed (1100) and voltage (165 V) have a mean value of the overcut or rough cut
of 1.50 by combining two factors. Similarly, Figs. 8, 11, 13 and 14, for the untreated and treated electrode, show the predicted values of TWR and Ra, respectively. Figures 7 to 16 and Table 10 confirm and validate the
experimental result mathematically. In this Table 10 takes optimal
values of factors, and the experiment for the untreated and deep
cryogenically treated electrode is performed again. Therefore from the above experiment, it can be seen that this experiment is valid and that the positive responses were confirmed for non-traditional EDM rather than traditional EDM.

Figure 17

(a, b) SEM images of the work piece
surface.

Figure 17a and b show SEM images of the work piece surface by using the
surface roughness optimal values (AI, BI and CI) of factors for both
traditional and non-traditional EDM respectively. The significant variables
labels are a current of 130 A, an electrode rotation of 1100 rpm (rpm – rotations per minute) and voltage of 90 V. Based on
the recast layer, globules and cracks are observed. The cracks are formed
due to thermal stress that is generated during machining. The Fig. 17a notation
image shows the work piece surface that is used for the untreated electrode,
and Fig. 17b shows the work piece surface that is used for the deep cryogenically treated electrode.

Figure 18

Percentage difference between traditional and non-traditional EDM.

Figure 19

Response factor chart.

Figure 17 shows that the globule size and crack size are smaller in
non-traditional than traditional or conventional EDM. Sizes of globules and
cracks affect the surface roughness. If the size of globules and cracks is smaller, then the surface roughness is also smaller. So the cryogenically treated
electrode has a more significant resultant than the untreated electrode
(conventional EDM). Figure 18 and Table 10 show the percentage difference
between the traditional and non-traditional EDM. The experiment performed by
taking the same levels for the untreated and cryogenically treated electrode
found that the overcut, tool wear rate and surface roughness were reduced by
9.12 %, 13.22 % and 15.75 % respectively in non-traditional EDM compared to
conventional EDM. Figure 19 shows which response factor is more
affected if the experiment is conducted with the deep cryogenically treated
electrode. The percentages affecting the response factors are 24 %,
35 % and 41 % for the overcut, tool wear rate and surface roughness
respectively. From the experiment that is represented in the form of a chart in
Figs. 18 and 19, surface roughness is found to have reduced more than the
other response factors. The percentage difference that can be calculated is given
below:
|1stvalue-2ndvalue|(1stvalue+2ndvalue)/2×100.
Other researchers have conducted an experiment on the cryogenic treatment for
different response factors with their evidence. Dhanachezian et al. (2011)
performed an experiment on cryogenic treatment with liquid nitrogen as
a cooling medium and found a reduction in the tool wear rate and surface
roughness compared to the conventional process. Huang et al. (2003) performed
an experiment on the cryogenic treatment for the M2-tool steel and concluded
that wear resistance improves due to the formation of the carbon cluster on the
surface of the electrode after cryogenic treatment. Collins and Jarmer (1997)
presented the results of cryogenic treatment and suggested a 29 % to 54 %
improvement in the case of MRR and a 0.7 % to 4 % reduction in the case of surface
roughness compared to the non-cryogenic treatment. Srivastava and Panday (2012) investigated an experiment on the M2-grade high-speed steel work piece
and found a 20 % reduction in the tool wear rate by cryogenic cooling of
the electrode. S. Kumar et al. (2014) found that the deep cryogenic treatment of
Titanium alloys increases the material removal rate while increasing the thermal
and electrical conductivity. Goyal et al. (2018) performed an experiment on
the AISI D2-tool steel with a copper electrode and found that the material removal
rate increased by approximately 18 % and surface roughness reduced by
11 % approximately with the cryogenic tool. Abdulkareem et al. (2010)
investigated the effect of electrode cooling on electrode wear. They
calculated that 14 % to 20 % of electrode wear can be reduced by using
optimal values of input parameters for cryogenic EDM.

3.5Significance of non-traditional EDM

Tool life is longer and no special tooling is required, so the tool cost decreases. Non-traditional EDM eliminates secondary finishing
operations because the surface roughness is less than traditional EDM. A thin wall
can be machined due to a smaller overcut in the deep cryogenically treated electrode than
in a normal electrode. Surface finish of product is good, and wastage of raw
material is less in the deep cryogenic treatment than in traditional EDM.

4Conclusion

The present experimental work is concerned with determining the optimum setting
of EDM to find the optimal overcut, TWR and Ra. L16 was used for performing the experiment.

The voltage and electrode rotation have the maximum effect on the radial
overcut (OC), also known as ROC, compared to the pulse current in the case of a non-cryogenic electrode. In the case of surface roughness for an untreated
electrode, the pulse current has a higher ranked effect than rotation and
voltage. Like in the tool wear rate, the pulse current has dominating effects.

Optimum parameters (for both cases) of the overcut are as follows: a current of 130 A, a rotation speed of 1100 rpm and a voltage of 165 V. The best fits for the tool wear
rate are a current of 210 A, an electrode rotation speed of 2100 rpm, and a voltage of 120 V.
In cases of surface roughness, 130 A, 1100 rpm and 90 V are the best levels with
respect to the current, rotation speed and voltage.

The pulse current and rotational speed are the most significant factors for the tool
wear rate and surface roughness in the case of the deep cryogenically treated electrode,
but in the case of the deep cryogenically treated electrode, for the overcut, only electrode
rotational speed has a larger effect.

The validation and confirmation test confirmed that the adequacy of a law of
additively is justified. The deep cryogenically treated electrode has a smaller
value of the overcut than the non-cryogenically electrode. So the deep cryogenically treated electrode (non-traditional) has larger effects on the response
factors than the traditional electrode; 9.12 % less overcut was found
in this experiment. In other words, approximately 9 % less overcut was produced in the cryogenically tempering-treated tool compared to the non-cryogenically treated tool.
In the case of the tool wear rate, the wear rate is reduced by 13.22 % with cryogenic
treatment. On the other hand, it was observed in the experiment that the surface
roughness was reduced by 15.75 % (approximately 15 % to 16 %) by using the deep
cryogenically treated electrode instead of the untreated electrode. So in the end,
it is found that machining has positive results after the cryogenic tempering
treatment of the electrode.

Deep cryogenic treatment improves the thermal conductivity of the tool and
reshapes carbide into a uniform and homogenous structure more frequently than the non-cryogenic tool.
Due to this, the power consumption and wear losses are reduced.
Therefore, the deep cryogenic tool is used as a priority base more than the non-cryogenic
tool where a high-speed-cutting operation was performed.

The deep cryogenic treatment improves tool life, so it reduces investment for the
purchase of new cutting tool; moreover less wear and tear decreased the
reshaping and regrinding of a tool, so it reduced the labour cost and ideal
time of machining to replace the tool. The deep cryogenically treated electrode
improves the quality and production rate more than the non-cryogenic electrode.

The experiment between the deep cryogenic and untreated electrode
represented non-traditional EDM being more effective and efficient than
the traditional EDM process.

GSG and DPD were responsible for problem finding, conceiving and designing the analysis, collecting the data, contributing data or analysis tools, conducting the experiment and receiving a fruitful result, performing the analysis, and writing the paper.

Competing interests

The authors declare that they have no conflict of interest.

Acknowledgements

Gurdev Singh Grewal would like to express his deep gratitude to his father S. Sukhdev Singh Grewal for guidance and financial support.

Review statement

This paper was edited by Xichun Luo and reviewed by Senthil Kumaran Selvaraj and one anonymous referee.